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This thesis uses mixed-methods to study key areas of concern in supply chain management for the improved delivery of humanitarian aid and the fight against dark supply chains, specifically human trafficking. The growing field of supply chain management finds some of its antecedents in the operations of war, business, and in the delivery of aid. These three areas employ similar supply chain management tools and are inextricably linked, yet prior research is compartmentalised with the study of one area at a time, often with the questionable assumption of altruistic objectives of the main actors. This thesis challenges such common notions by providing new insights on: • supply chain vulnerabilities that span across industries, • an objective of stopping a supply chain rather than improving it, and • an understanding of how to disrupt human trafficking supply chains. To begin, I perform a literature survey to outline the key humanitarian areas that can benefit from further research in supply chain management (Chapter 1). This extends the realm of humanitarian research to include dark (i.e. hidden) supply chains as a field of study. To better understand dark supply chains, I employ multiple methodologies which are introduced in Chapter 2. I provide an exposition of the operational methods of dark supply chains in Chapter 3. In Chapter 4, I use game theory to analyse established industry and government protocols to optimise the decisions that underpin supply chain regulation on forced labour. In order to combat human trafficking supply chains, I use econometrics to study historical supply chain failures and categorise their vulnerabilities in Chapter 5. Chapter 6 applies the findings from the previous chapters to the dark supply chains involved in the case of illegal gold mining in Peru. The thesis ends with discussion and relevant directions for future research in supply chain management.

Neural mechanisms for learning are largely conserved across taxa, and with relatively simple, modularly organized nervous systems, crustaceans have proven a suitable model for exploring its cellular basis. Associative learning, in particular, is necessary for animals to gain predictability about their surroundings and to display stimulus-appropriate behavior. Crayfish have previously demonstrated the capability to learn through classical conditioning and they possess many traits desirable in a research model, such as the ability to engage in highly structured behaviors using a number of different, specialized appendages. The present study extends these findings to instrumental learning. We have successfully designed and implemented a spatially contingent, operant paradigm in which crayfish learned to avoid a particular substrate that is paired with electro shock punishment. Animals quickly responded with altered substrate preference and a marked change in locomotor activity.